Construction of Marine Surface Pressure Fields from Scatterometer Winds Alone

Abstract

A series of six-hourly, synoptic, gridded, global surface wind fields with a resolution of 100 km has been generated using the dataset of dealiased Seasat satellite scatterometer (SASS) winds produced as described by Peteherych et al. (1984). This paper k an account of the construction of surface pressure fields from these SASS synoptic wind fields only, as carried out by different methods, and the comparison of these pressure fields with U. S. National Centers for Environmental Prediction (NCEP) analyses, with the pressure fields of the European Centre for Medium Range Weather Forecasting (ECMWF) and with the special analyses of the Gulf of Alaska Experiment (GOASEX). One of the methods we use to derive the pressure fields utilizes a two-layer planetary boundary layer (PBL) model iterative scheme that relates the geostrophic wind vector to the surface wind vector, surface roughness, humidity, diabatic and baroclinic effects and secondary flow. A second method involves the assumption of zero twodimensional divergence, leading to a Poisson equation (the 'balance equation') in pressure, with the wind field serving as a forcing function. The pressure fields computed from the SASS winds using a two-layer PBL model closely approximate the N.MC and ECMWF fields. In some cases, the PBL-modelderived pressure fields can detect mesoscale features not resolved in either the N.MC or ECMWF analyses. Balanced-pressure fields are much smoother and less well resolved than the PBL-model-derived or NIMC fields. Systematic differences between balanced pressure fields and the PBL-model-derived fields are attributed to the neglect of. horizontal divergence in the balance equation. The effect of stratification is found to produce a larger impact than secondary flow or thermal wind effects on the derived pressure fields. Inclusion of secondary flow tends to weaken both low and high pressure

Satellite‐based midlatitude cyclone statistics over the Southern Ocean: 1. Scatterometer‐derived pressure fields and storm tracking

“…There exist various methods for estimating the surface pressure field from surface wind vectors [ Brown and Levy , 1986; Harlan and O'Brien , 1986; Hsu et al , 1997; Hsu and Liu , 1996; Zierden et al , 2000; Hilburn et al , 2003; Patoux et al , 2003, 2008]. The satellite‐based surface pressure fields used in this study and referred to, here, as the University of Washington QuikSCAT (UWQS) pressure fields, are derived from QS measurements using the method described by Brown and Levy [1986] and Patoux et al [2003].…”

On satellite scatterometer model functions

“…The success of the wind product led Brown, Levy, and Zeng and others [Brown and Levy, 1986;Harlan and O'Brien, 1986;Levy and Brown, 1991;Brown and Zeng, 1994;Hsu and Liu, 1996;Hsu et al, 1997;Zeng and Brown, 1998] to calculate surface pressure fields from scatterometer surface winds. When the calculations are done with vectors using a state-ofthe-art PBL model [Brown and Levy, 1986], these fields were shown to agree remarkably well with the European Centre for Medium-Range Weather Forecasts (ECMWF) and National Centers for Environmental Prediction (NCEP) analyses.…”

Retrieval of Barometric Pressure from Satellite Passive Microwave Observations over the Oceans

“…Such accuracy is daunting in remote sensing techniques. Consequently, greater effort has been put into obtaining the surface pressure gradient fields via surface winds measured by scatterometers rather than the surface pressure itself (Brown & Levy, ; Hsu et al, ; Patoux et al, ). Unfortunately, the output of this methodology is a pressure gradient so that at least one reliable observation (e.g., buoy or coastal station) is required to produce the absolute pressure field.…”